NASA and John Deere spread self-driving tractor capabilities

spinonews self-driving tractor

NASA and John Deere spread self-driving tractor capabilities

More than a decade ago, farmers using self-driving tractor in part of partnership between John Deere and NASA’s Jet Propulsion Laboratory (JPL) on GPS receivers.

The company, John Deere, combined GPS location data with readings from sensors on a harvesting combine to determine the crop yield on different parts of the field. Such information can help farmers allocate future resources and determine which seed varieties and management practices are the most productive.

But John Deere wanted to create a system that could guide the tractor autonomously. The test uncorrected GPS can be off by up to about 30 feet due to data errors, drift in the GPS satellites’ internal clocks, and inaccurate orbital parameters.

John Deere modifies its StarFire GPS

Scientists at JPL already working on a crucial tool to stream satellite tracking data in real time via Internet. While, John Deere is working on its own technology for correcting GPS signals in cooperation with another company, NavCom. Moreover, it was costly and required introducing at least one flag towers.

In 2004, John Deere modifies its StarFire GPS receivers and incorporate JPL’s software for its GPS-correction software and a contract to receive data from JPL’s global network of reference stations.

The JPL-linked system was exact down to a few inches, also with this solution, John Deere could finally offer self-driving agricultural equipment to its customers worldwide.

Normally, when a tractor confuses a field, the lines cover by around 10%. This implies a critical segment of the field gets double the important seed, fertilizer, and pesticide, and the job takes longer than necessary.

Eliminating overlap also cuts down on fuel costs, wear and tear on the machinery, and tractor operator time, since an operator is required to monitor operating conditions and avoid collisions. What’s more, higher accuracy, means more reliable yield maps.